
000 | 00000cam u2200205 a 4500 | |
001 | 000045855215 | |
005 | 20151228170747 | |
008 | 151228s2012 nyua 000 0 eng d | |
010 | ▼a 2011410897 | |
020 | ▼a 9780071790536 (pbk.) | |
020 | ▼a 0071790535 (pbk.) | |
035 | ▼a (KERIS)REF000017910912 | |
040 | ▼a BTCTA ▼b eng ▼c BTCTA ▼d SINLB ▼d YDXCP ▼d SUF ▼d BWX ▼d OCLCQ ▼d DLC ▼d 211009 | |
050 | 0 0 | ▼a QA76 ▼b .Z55 2012 |
082 | 0 4 | ▼a 005.74 ▼2 23 |
084 | ▼a 005.74 ▼2 DDCK | |
090 | ▼a 005.74 ▼b U55 | |
245 | 0 0 | ▼a Understanding big data : ▼b analytics for enterprise class Hadoop and streaming data / ▼c Paul C. Zikopoulos ... [et al.]. |
260 | ▼a New York : ▼b McGraw-Hill, ▼c 2012. | |
300 | ▼a xxxi, 141 p. : ▼b ill. ; ▼c 23 cm. | |
520 | ▼a "Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data-volume, variety, and velocity-are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide."-- ▼c Page 4 of cover. | |
630 | 0 0 | ▼a Apache Hadoop (Computer file). |
650 | 0 | ▼a Electronic data processing ▼x Distributed processing. |
650 | 0 | ▼a File organization (Computer science). |
650 | 0 | ▼a Data mining. |
700 | 1 | ▼a Zikopoulos, Paul. |
945 | ▼a KLPA |
소장정보
No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
---|---|---|---|---|---|---|---|
No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 005.74 U55 | 등록번호 121235143 | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |